resources, it is critical to choose the best set of observations or experimental conditions with which to probe a system. Here, new computational tools can rigorously quantify the information value of an experiment with regard to particular parameters or performance metrics of interest, before the experiment is actually performed. Optimal experiments can then be chosen sequentially as part of the model construction process. For example, we have used optimal experimental design to choose mixture conditions in shock tube ignition experiments, to more efficiently learn chemical kinetic mechanisms for the combustion of alternative fuels. TOWARDS SUSTAINABLE DECISIONS As we work towards revolutionary improvements in aerospace systems’ energy efficiency and environmental impact, computational engineering will play a key role guiding the design effort. In addition, future aerospace systems will incorporate unprecedented levels of automation to achieve environmental performance targets, requiring computational methods for real-time planning and control.
Computation can be used to optimize the collection of experimental data by identifying the measurements that will be most informative about selected quantities of interest. Shown above are contours of expected information gain in the kinetic parameters of a hydrogen-oxygen system, resulting from a measurement of ignition delay. The axes of the figure describe the two design variables of the ignition experiment: T is the initial temperature and φ is the fuel-air equivalence ratio of the combustible mixture. (X. Huan, Y. Marzouk image)
One area in which computational engineering is integral is the design of future aircraft to satisfy stringent environmental constraints on noise, air quality, and global emissions. These requirements necessitate the use of advanced technologies and novel configurations, which, in turn, demand high fidelity, physics-based design tools that do not rely heavily on empiricism and past experience. High-fidelity tools, such as computational fluid dynamics and finite element structural models, have become commonplace as analysis tools. However, a high-fidelity simulationbased design capability at the integrated aircraft system level remains out of reach. Aerospace Computational Design Lab researchers are tackling many aspects of this problem with a spectrum of research projects. These projects include developing the next generation of
Confronting energy and environment’s toughest challenges with computational engineering
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